Odisha Craft – crafting the right expansion strategy

Learning outcomes Familiarize with the retail operations of handicrafts, facility location problem, apply multi-criteria decision through the goal programming approach and solving the same with MS Excel. Case overview / synopsis The case portrays a dilemma in the context of retail operations of a small-scale handicraft company known as Odisha Craft. Located in Odisha, Susanta Mohanty, the owner, was finding it a challenge to decide on the most promising location for his new retail outlet in the neighbouring city of Kolkata. He had five choices for the locations. Odisha craft was established by his father-in-law in 2009 with an objective to preserve and promote the rich culture of the handicrafts designed by the local artisans and ensure sustainable rural livelihood. The company had been facing numerous challenges and the pandemic has given a very formidable blow to the monthly revenues. The case brings out the multi-faceted dilemma of deciding on the facility location in 2020, involving a set of conflicting criteria. The case unfolds a systematic solution approach resolving the dilemma using MS Excel. Complexity academic level Courses such as operations research, operations management, service operations and retail operations for MBA students and trainings for junior-middle level executives. Supplementary materials Teaching notes are available for educators only. Subject code CSS 09: Operations and Logistics

Future Large Earthquake Analysis of Sulawesi Island Using Satellite Images and Moment Tensor Solution Approach

Sulawesi Island is the active tectonic region, where the tectonic architecture and potential earthquake sources until now remain largely unknown. The worst earthquake, an Mw 7.5 on September 28, 2018, in Palu, Indonesia, was caused catastrophic damage to life and property. The earthquake has highlighted the urgent need to raise knowledge of the cause of possible large future earthquakes and vulnerability. The main objective for this project is to create a thorough earthquake probabilistic hazard analysis map of the region, which is presently unavailable to better prepare for future earthquakes. The neotectonic and structural map was created using was supplemented with the 30-m resolution Shuttle Radar Topography Mission, Centroid Moment Tensor (CMT) solution, and seismologic data. The results demonstrate that faulting controls the geometry and the majority of these faults are active and capable of causing medium to large magnitude earthquakes with moment magnitudes ranging from 6.2 to 7.5 from 44 seismic sources. Our results show Sulawesi's northern deformation regimes have high seismicity risk and vulnerability. This study contributes a realistic seismic source for the Sulawesi neotectonic area particularly at the northwest, north, and east deformation regime, to understand the key large future earthquakes.

The Flexible Scheduled Service Network Design Problem

The scheduled service network design problem (SSNDP) can support planning the transportation operations of consolidation carriers given shipment-level service commitments regarding available and due times. These available and due times impact transportation costs by constraining potential consolidation opportunities. However, such available and due times may be changed, either because of negotiations with customers or redesigned internal operations to increase shipment consolidation and reduce transportation costs. As changing these times can lead to customer service and operational issues, we presume a carrier seeks to do so for a limited number of shipments. We propose a new variant of the SSNDP, the flexible scheduled service network design problem, that identifies the shipments for which these times should be changed to minimize total transportation and handling costs. We present a solution approach for this problem that outperforms a commercial optimization solver on instances derived from the operations of a U.S. less-than-truckload freight transportation carrier. With an extensive computational study, we study the savings potential of leveraging flexibility and the operational settings that are fertile ground for doing so.

Blockchain-IoT peer device storage optimization using an advanced time-variant multi-objective particle swarm optimization algorithm

The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements. A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time-variant Multi-objective Particle Swarm Optimization Algorithm (AT-MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time-variant weights for the velocity of the particle swarm optimization and the non-dominated sorting and mutation schemes from NSGA-III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA-II), and the Pareto Envelope-based Selection Algorithm with region-based selection (PESA-II), and NSGA-III. The proposed AT-MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT-MOPSO achieved 52% energy efficiency compared to NSGA-III. To show how this algorithm can be applied to a real-world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT-MOPSO can be used with existing Blockchain systems and the benefits it provides.

Social Entrepreneurship In MSME Development

The creative industry through community-based industry on the scale of MSMEs, has developed quite well. The creative industry has the opportunity to continue to increase, because the industry is responsive to absorb the accumulation of social phenomena in society and pour it into the context of products and services. The problems faced by MSMEs are still homework, the problems include fulfilling the market aspect, which is caused by the availability of the goods produced. This study aims to obtain problem information and the right solution approach in answering the existing problems. The results of the study indicate that the problem of human resource availability can be done with alternative solutions in the form of a social entrepreneurship approach with the involvement of the community around the industry

Robot-Based Last-Mile Deliveries With Pedestrian Zones

Since delivery robots share sidewalks with pedestrians, it may be beneficial to choose paths for them that avoid zones with high pedestrian density. In this paper, we investigate a robot-based last-mile delivery problem considering path flexibility given the presence of zones with varying pedestrian level of service (LOS). Pedestrian LOS is a measure of pedestrian flow density. We model this new problem with stochastic travel times and soft customer time windows. The model includes an objective that reflects customer service quality based on early and late arrivals. The heuristic solution approach uses the minimum travel time paths from different LOS zones (path flexibility). We demonstrate that the presence of pedestrian zones leads to alternative path choices in 30% of all cases. In addition, we find that extended time windows may help increase service quality in zones with high pedestrian density by up to 40%.

A GRASP-Based Approach for Planning UAV-Assisted Search and Rescue Missions

Search and Rescue (SAR) missions aim to search and provide first aid to persons in distress or danger. Due to the urgency of these situations, it is important to possess a system able to take fast action and effectively and efficiently utilise the available resources to conduct the mission. In addition, the potential complexity of the search such as the ruggedness of terrain or large size of the search region should be considered. Such issues can be tackled by using Unmanned Aerial Vehicles (UAVs) equipped with optical sensors. This can ensure the efficiency in terms of speed, coverage and flexibility required to conduct this type of time-sensitive missions. This paper centres on designing a fast solution approach for planning UAV-assisted SAR missions. The challenge is to cover an area where targets (people in distress after a hurricane or earthquake, lost vessels in sea, missing persons in mountainous area, etc.) can be potentially found with a variable likelihood. The search area is modelled using a scoring map to support the choice of the search sub-areas, where the scores represent the likelihood of finding a target. The goal of this paper is to propose a heuristic approach to automate the search process using scarce heterogeneous resources in the most efficient manner.